Bipolar disorder in the balance
- 84 Downloads
Bipolar disorder (BD) is a severe mood disorder that lacks established electrophysiological, neuroimaging or biological markers to assist with both diagnosis and monitoring disease severity. This study’s aim is to describe the potential of new neurophysiological features assistive in BD diagnosis and severity measurement utilizing the recording of electrical activity from the outer ear canal called Electrovestibulography (EVestG). From EVestG data sensory vestibulo-acoustic features were extracted from a single supine-vertical translation stimulus to distinguish 50 depressed and partly remitted/remitted bipolar disorder patients [18 symptomatic (BD-S, MADRS > 19), 32 reduced symptomatic (BD-R, MADRS ≤ 19)] and 31 age and gender matched healthy individuals (controls). Six features were extracted from the measured firing pattern interval histogram and the extracted shape of the average field potential response. Five of the six features had low but significant correlations (p < 0.05) with the MADRS assessment. Using leave-one-out-cross-validation, unbiased parametric and non-parametric classification routines resulted in 75–79%, 84–86%, 76–85% and 79–82% accuracy for separation of control from BD, BD-S and BD-R as well as BD-S from BD-R groups, respectively. The main limitation of this study was the inability to fully disentangle the impact of prescribed medication from the responses recorded. A mix of stationary and movement evoked EVestG features produced good discrimination between control and BD patients whether BD-S or BD-R. Moreover, BD-S and BD-R appear to have measurably different pathophysiological manifestations. The firing pattern features used were dissimilar to those observed in a prior major depressive disorder study.
KeywordsBipolar disorder Depression Neurobiology Electrovestibulography Biological markers Vestibular
- Background phase
1.5 s EVestG recording immediately prior to motion
Bipolar disorder, (-S) symptomatic, (-R) reduced symptomatic (-R can be broken into (-M) mild and (-A) asymptomatic)
- IH1, IH2
EVestG short interval features. Intervals were the time between detected FP’s
- IH331, IH332
EVestG long interval features. Intervals were the time between each 33rd FP
Linear discriminant analysis
Montgomery Asberg Depression Rating Scale
Major depressive disorder, (-S) symptomatic, (-R) reduced symptomatic
Mood stabilizer medication
Neural event extraction routine
- Acceleration phase
1.5 s EVestG recording during the acceleration phase
- Deceleration phase
1.5 s EVestG recording during the deceleration phase
- Sh1, Sh2
EVestG shape features
We would like to thank all members of Monash Alfred Psychiatry Research Center who supported this research. Amber Garrett (a Ph.D. student) recorded many of the EVestG recordings. This work was supported by grants from the Australian Research Council and National Health and Medical Research Council. Neural Diagnostics Pty Ltd was the industry partner in this research. PF is supported by an NHMRC practitioner fellowship.
BL wrote the first draft and did main data analysis; ZM and PF were the major contributors to the data analysis and paper writing; BL, PF, JK and CG conceived the experiment(s). PF and JK examined and referred the patients. CG and JM contributed to patient assessments. All authors reviewed the manuscript.
Funding was provided by Australian Research Council (Grant no. LP0669420).
Compliance with ethical standards
Conflict of interest
BL owns < 0.5% of shares in Neural Diagnostics Pty Ltd. (ND) and acts as a part-time consultant for ND. PF is supported by a NHMRC Practitioner Fellowship (1078567). PF has received equipment for research from MagVenture A/S, Medtronic Ltd, Cervel Neurotech and Brainsway Ltd and funding for research from Neuronetics and Cervel Neurotech. He is on the scientific advisory board for Bionomics Ltd. ZM, CG, JM, JK report no financial interests or potential conflicts of interest.
- 19.Lithgow BJ (2012) A methodology for detecting field potentials from the external ear canal: NEER and EVestG. Ann BME 40(8):1835–1850Google Scholar
- 25.Heibert D (2010) Computer models of the vestibular head tilt response, and their relationship to EVestG and Meniere’s disease. Doctor of Philosophy, Monash UniversityGoogle Scholar
- 30.Niculescu AB (2013) Convergent functional genomics of psychiatric disorders. Am J Med Genet Part B 9999:1–7Google Scholar
- 33.Soreff S (2013) Medscape: bipolar disorder-etiology and pathophysiology. http://emedicine.medscape.com/article/286342-overview#a0104. Accessed 14 Mar 2014
- 46.Benes FM (2012) Nicotinic receptors and functional regulation of GABA cell microcircuitry in bipolar disorder and schizophrenia. In: Geyer MA, Goss G (eds) Handbook of experimental pharmacology: novel antischizophrenia treatments, vol 213. Springer, BerlinGoogle Scholar